I want to simulate a model in Dymola in real-time for HiL use. In the results I see that the Simulation is advancing about 5% too fast.
Integration terminated successfully at T = 691200
CPU-time for integration : 6.57e+005 seconds
CPU-time for one GRID interval: 951 milli-seconds
I already tried to increase the grid interval to reduce the relativ error, but still the simulation is advancing too fast. I only read about aproaches to reduce model complexity to allow simulation within the defined time steps.
Note, that the Simulation does keep up with real-time and is even faster. How can I ín this case match simulated time and real time?
Edit 1:
I used Lsodar solver with checked "Synchronize with realtime option" in Realtime tab. I have the realtime simulation licence option. I use Dymola 2013 on Windows 7. Here the result for a stepsize of 15s:
Integration terminated successfully at T = 691200
CPU-time for integration : 6.6e+005 seconds
CPU-time for one GRID interval : 1.43e+004 milli-seconds
The deviation still is roughly about 4.5%.
I did however not use inline integration.
Do I need hard realtime or inline integration to improve those results? It should be possible to get a deviation lower than 4.5% using soft realtime or not?
Edit 2:
I took the Python27 block from the Berkeley Buildings library to read the System time and compare it with the Simulation advance. The result shows that 36 hours after Simulation start, the Simulation slows down slightly (compared to real time). About 72 hours after the start of the simulation it starts getting about 10% faster than real time. In addition, the jitter in the result increases after those 72 hours.
Any explanations?
Next steps will be:
-changing to fixed step solver (Might well be this is a big part of the solution)
-Changing from DDE Server to OPC Server, which at the Moment doesn't not seem to be possible in Dymola 2013 however.
Edit 3:
Nope... using a fixed step solver does seem to solve the problem. In the first 48 hours of simulation time the deviation seems to be equal to the deviation using a solver with variable step size. In this example I used the Rkfix 3 solver with an integrator step of 0.1.
Nobody knows how to get rid of those huge deviations?
If I recall correctly, Dymola has a special compilation option for real-time performance. However, I think it is a licensed option (not sure).
I suspect that Dymola is picking up the wrong clock speed.
You could use the "Slowdown factor" that is in the Simulation Setup, on the Realtime tab just below "Synchronize with realtime". Set this to 1/0.95.
There is a parameter in Dymola that you can use to set the CPU speed but I could not find this now, I will have a look for this again later.
I solved the problem switching to an embedded OPC-Server. Error between real time and simulation time in this case is shown below.
Compiling Dymola Problems with an embedded OPC-Server requires administrator rights (which I did not have before). The active folder of Dymola must not be write protected.
Related
I have a DAQ for Temperature measurment. I take a continuous sample rate and after DAQ, calculating temperature difference per minute (Cooling Rate: CR) during this process. This CR and temperature values are inserted into the Matlab script for a physical model running (predicting the temperature drop for next 30 sec). Then, I record and compare the predicted and experimental values in LabVIEW.
What i am trying to do is the matlab model is executing every 30 sec, and send out its predictions as an output from matlab script. One of this outputs helps me to change the Air Blower Motor Speed until next matlab run( eventually affect the temperature drop for next 30 sec as well, which becomes a closed loop). After 30 sec while main process is still running, sending CR and temperature values to matlab model again, and so on.
I have a case structure for this Matlab script. And inside of case structure i applied an elapsed time function to control the timing for the matlab script, but this is not working.
Yes. Short answer: I believe (one of) the reasons the program behaves weird on changed timing are several race conditions present in the code.
The part of the diagram presented shows several big problems with the code:
Local variables lead to race conditions. Use dataflow. E.g. you are writing to Tinitial local variable, and reading from Tinitial local varaible in the chunk of code with no data dependencies. It is not known whether reading or writing will happen first. It may not manifest itself badly with small delays, while big delays may be an issue. Solution: rewrite you program using the following example:
From Bad:
To Good:
(nevermind broken wires)
Matlab script node executes in the main UI execution system. If it is executing for a long time, it may freeze indicators/controls as well as execution of other pieces of code. Change execution system of other VIs in your program (say to "other 1") and see if the situation improves.
I ran the profiler on my Simulink model and realized that the "To Workspace" block is using 20% of the total simulation time. Because this model is ran more than one time, I'm looking for a way to increase its performance.
Hence, is there an alternate solution to using the "To Workspace" block that would increase my model global performance?
Yes, you can use Signal Logging. The various approaches to logging simulation results are discussed in the documentation under Export Simulation Data. Finally, see also View Simulation Results for alternative approaches. My personal recommendation would be signal logging or a To File block.
According to my general understanding of memory management, reserving a fixed memory block takes less time than expanding it in each timestep. So, it might be useful to limit the number of data points to be logged, that the memory space reserved for your data set will not be dynamically increased at every timestep. Of course this would be only valid if you would know the number of data points and therefore number of steps in simulation prior to start of the simulation, which can be achieved by a fixed step size solver (if applicable by your simulation system setuo). Thus pre-allocation of the workspace array might save you some time in terms of not reaching the memory management system at each timestep.
I want to run a simulation which includes SimEvent blocks (thus only Normal option is available for sim run) for a large number of times, like at least 1000. When I use sim it compiles the program every time and I wonder if there is any other solution which just run the simulation repeatedly in a faster way. I disabled Rebuild option from Configuration Parameter and it does make it faster but still takes ages to run for around 100 times.
And single simulation time is not long at all.
Thank you!
It's difficult to say why the model compiles every time without actually seeing the model and what's inside it. However, the Parallel Computing Toolbox provides you with the ability to distribute the iterations of your model across several cores, or even several machines (with the MATLAB Distributed Computing Server). See Run Parallel Simulations in the documentation for more details.
I'm working on an adaptive and Fully automatic segmentation algorithm under varying light condition , the core of this algorithm uses Particle swarm Optimization(PSO) to tune the fuzzy system and believe me it's very time consuming :| for only 5 particles and 100 iterations I have to wait 2 to 3 hours ! and it's just processing one image from my data set containing over 100 photos !
I'm using matlab R2013 ,with a intel coer i7-2670Qm # 2.2GHz //8.00GB RAM//64-bit operating system
the problem is : when starting the program it uses only 12%-16% of my CPU and only one core is working !!
I've searched a lot and came into matlabpool so I added this line to my code :
matlabpool open 8
now when I start the program the task manger shows 98% CPU usage, but it's just for a few seconds ! after that it came back to 12-13% CPU usage :|
Do you have any idea how can I get this code run faster ?!
12 Percent sounds like Matlab is using only one Thread/Core and this one with with full load, which is normal.
matlabpool open 8 is not enough, this simply opens workers. You have to use commands like parfor, to assign work to them.
Further to Daniel's suggestion, ideally to apply PARFOR you'd find a time-consuming FOR loop in you algorithm where the iterations are independent and convert that to PARFOR. Generally, PARFOR works best when applied at the outermost level possible. It's also definitely worth using the MATLAB profiler to help you optimise your serial code before you start adding parallelism.
With my own simulations I find that I cannot recode them using Parfor, the for loops I have are too intertwined to take advantage of multiple cores.
HOWEVER:
You can open a second (and third, and fourth etc) instance of Matlab and tell this additional instance to run another job. Each instance of matlab open will use a different core. So if you have a quadcore, you can have 4 instances open and get 100% efficiency by running code in all 4.
So, I gained efficiency by having multiple instances of matlab open at the same time and running a job. My jobs took 8 to 27 hours at a time, and as one might imagine without liquid cooling I burnt out my cpu fan and had to replace it.
Also do look into optimizing your matlab code, I recently optimized my code and now it runs 40% faster.
I am trying to run a real-time simulation in Simulink using Real-time Workshop. The target is grt(I have tried rtwin, but my simulation refuses to compile for it). I need the simulation to run in real-time so that one second in simulation lasts one second of real time. Grt ignores realtime and finishes the simulation in shortest time possible. Is there any way to synchronise it?
I have tried http://www.mathworks.com/matlabcentral/fileexchange/3175 but could not get it to work(does not compile).
Thank you for any suggestions.
Looks like it is impossible. I was able to slow down the execution by using Sleep(time in ms) function from WinApi and clock function from time.h, which looked quite good for low sample rates. However, when I increased the sample rate the Sleep function was sleeping for too long, which resulted in errors, with one second in simulation lasting more than one real world second.
The idea was to say that one period of iteration should last, let's say 200ms. Then time how long it takes for one iteration of code to execute using the clock function. Then call Sleep(200 - u), where u is the length of the iteration. The problem is that Sleep function sleeps the process and wakes it up when it wants to, not when you tell it to in the argument.
I know this is not a solution, but post this so that if anyone faces the same problem as me they won't try this dead-end solution. I had to rewrite the simulation for rtwin and now it works fine.
Another idea would be to somehow use interrupts, but I guess it would be quite complicated and not worth the trouble.